OpenRaiser/Intern-Atlas huggingface dataset:
On graph classes with logarithmic boolean-width
Venue: arXiv cs.DM 2011
Year: 2011

Boolean-width is a recently introduced graph parameter. Many problems are fixed parameter tractable when parametrized by boolean-width, for instance "Minimum Weighted Dominating Set" (MWDS) problem can be solved in $O^*(2^{3k})$ time given a boolean-decomposition of width $k$, hence for all graph classes where a boolean-decomposition of width $O(\log n)$ can be found in polynomial time, MWDS can be solved in polynomial time. We study graph classes having boolean-width $O(\log n)$ and problems solvable in $O^*(2^{O(k)})$, combining these two results to design polynomial algorithms. We show that for trapezoid graphs, circular permutation graphs, convex graphs, Dilworth-$k$ graphs, circular arc graphs and complements of $k$-degenerate graphs, boolean-decompositions of width $O(\log n)$ can be found in polynomial time. We also show that circular $k$-trapezoid graphs have boolean-width $O(\log n)$, and find such a decomposition if a circular $k$-trapezoid intersection model is given. For many of the graph classes we also prove that they contain graphs of boolean-width $Θ(\log n)$. Further we apply the results from \cite{boolw2} to give a new polynomial time algorithm solving all vertex partitioning problems introduced by Proskurowski and Telle \cite{TP97}. This extends previous results by Kratochvíl, Manuel and Miller \cite{KMM95} showing that a large subset of the vertex partitioning problems are polynomial solvable on interval graphs.
Artificial Neural Networks, Symmetries and Differential Evolution
Venue: arXiv cs.NE 2011
Year: 2011

Neuroevolution is an active and growing research field, especially in times of increasingly parallel computing architectures. Learning methods for Artificial Neural Networks (ANN) can be divided into two groups. Neuroevolution is mainly based on Monte-Carlo techniques and belongs to the group of global search methods, whereas other methods such as backpropagation belong to the group of local search methods. ANN's comprise important symmetry properties, which can influence Monte-Carlo methods. On the other hand, local search methods are generally unaffected by these symmetries. In the literature, dealing with the symmetries is generally reported as being not effective or even yielding inferior results. In this paper, we introduce the so called Minimum Global Optimum Proximity principle derived from theoretical considerations for effective symmetry breaking, applied to offline supervised learning. Using Differential Evolution (DE), which is a popular and robust evolutionary global optimization method, we experimentally show significant global search efficiency improvements by symmetry breaking.
Restricted strong convexity and weighted matrix completion: Optimal bounds with noise
Venue: arXiv cs.IT 2011
Year: 2011

We consider the matrix completion problem under a form of row/column weighted entrywise sampling, including the case of uniform entrywise sampling as a special case. We analyze the associated random observation operator, and prove that with high probability, it satisfies a form of restricted strong convexity with respect to weighted Frobenius norm. Using this property, we obtain as corollaries a number of error bounds on matrix completion in the weighted Frobenius norm under noisy sampling and for both exact and near low-rank matrices. Our results are based on measures of the "spikiness" and "low-rankness" of matrices that are less restrictive than the incoherence conditions imposed in previous work. Our technique involves an $M$-estimator that includes controls on both the rank and spikiness of the solution, and we establish non-asymptotic error bounds in weighted Frobenius norm for recovering matrices lying with $\ell_q$-"balls" of bounded spikiness. Using information-theoretic methods, we show that no algorithm can achieve better estimates (up to a logarithmic factor) over these same sets, showing that our conditions on matrices and associated rates are essentially optimal.
Semantics of Typed Lambda-Calculus with Constructors
Venue: arXiv cs.LO 2011
Year: 2011

We present a Curry-style second-order type system with union and intersection types for the lambda-calculus with constructors of Arbiser, Miquel and Rios, an extension of lambda-calculus with a pattern matching mechanism for variadic constructors. We then prove the strong normalisation and the absence of match failure for a restriction of this system, by adapting the standard reducibility method.
Reduced Complexity Decoding for Bit-Interleaved Coded Multiple Beamforming with Constellation Precoding
Venue: arXiv cs.IT 2011
Year: 2011

Multiple beamforming is realized by singular value decomposition of the channel matrix which is assumed to be known to both the transmitter and the receiver. Bit-Interleaved Coded Multiple Beamforming (BICMB) can achieve full diversity as long as the code rate Rc and the number of employed subchannels S satisfy the condition RcS<=1. Bit-Interleaved Coded Multiple Beamforming with Constellation Precoding (BICMB-CP), on the other hand, can achieve full diversity without the condition RcS<=1. However, the decoding complexity of BICMB-CP is much higher than BICMB. In this paper, a reduced complexity decoding technique, which is based on Sphere Decoding (SD), is proposed to reduce the complexity of Maximum Likelihood (ML) decoding for BICMB-CP. The decreased complexity decoding achieves several orders of magnitude reduction, in terms of the average number of real multiplications needed to acquire one precoded bit metric, not only with respect to conventional ML decoding, but also, with respect to conventional SD.
Exploiting Channel Memory for Joint Estimation and Scheduling in Downlink Networks
Venue: arXiv cs.NI 2011
Year: 2011

We address the problem of opportunistic multiuser scheduling in downlink networks with Markov-modeled outage channels. We consider the scenario in which the scheduler does not have full knowledge of the channel state information, but instead estimates the channel state information by exploiting the memory inherent in the Markov channels along with ARQ-styled feedback from the scheduled users. Opportunistic scheduling is optimized in two stages: (1) Channel estimation and rate adaptation to maximize the expected immediate rate of the scheduled user; (2) User scheduling, based on the optimized immediate rate, to maximize the overall long term sum-throughput of the downlink. The scheduling problem is a partially observable Markov decision process with the classic 'exploitation vs exploration' trade-off that is difficult to quantify. We therefore study the problem in the framework of Restless Multi-armed Bandit Processes (RMBP) and perform a Whittle's indexability analysis. Whittle's indexability is traditionally known to be hard to establish and the index policy derived based on Whittle's indexability is known to have optimality properties in various settings. We show that the problem of downlink scheduling under imperfect channel state information is Whittle indexable and derive the Whittle's index policy in closed form. Via extensive numerical experiments, we show that the index policy has near-optimal performance. Our work reveals that, under incomplete channel state information, exploiting channel memory for opportunistic scheduling can result in significant performance gains and that almost all of these gains can be realized using an easy-to-implement index policy.
Performance Analysis and Design of Two Edge Type LDPC Codes for the BEC Wiretap Channel
Venue: arXiv cs.IT 2011
Year: 2011

We consider transmission over a wiretap channel where both the main channel and the wiretapper's channel are Binary Erasure Channels (BEC). We propose a code construction method using two edge type LDPC codes based on the coset encoding scheme. Using a standard LDPC ensemble with a given threshold over the BEC, we give a construction for a two edge type LDPC ensemble with the same threshold. If the given standard LDPC ensemble has degree two variable nodes, our construction gives rise to degree one variable nodes in the code used over the main channel. This results in zero threshold over the main channel. In order to circumvent this problem, we numerically optimize the degree distribution of the two edge type LDPC ensemble. We find that the resulting ensembles are able to perform close to the boundary of the rate-equivocation region of the wiretap channel. There are two performance criteria for a coding scheme used over a wiretap channel: reliability and secrecy. The reliability measure corresponds to the probability of decoding error for the intended receiver. This can be easily measured using density evolution recursion. However, it is more challenging to characterize secrecy, corresponding to the equivocation of the message for the wiretapper. Méasson, Montanari, and Urbanke have shown how the equivocation can be measured for a broad range of standard LDPC ensembles for transmission over the BEC under the point-to-point setup. By generalizing the method of Méasson, Montanari, and Urbanke to two edge type LDPC ensembles, we show how the equivocation for the wiretapper can be computed. We find that relatively simple constructions give very good secrecy performance and are close to the secrecy capacity. However finding explicit sequences of two edge type LDPC ensembles which achieve secrecy capacity is a more difficult problem. We pose it as an interesting open problem.
Spectrum Sharing between Cooperative Relay and Ad-hoc Networks: Dynamic Transmissions under Computation and Signaling Limitations
Venue: arXiv cs.IT 2011
Year: 2011

This paper studies a spectrum sharing scenario between a cooperative relay network (CRN) and a nearby ad-hoc network. In particular, we consider a dynamic spectrum access and resource allocation problem of the CRN. Based on sensing and predicting the ad-hoc transmission behaviors, the ergodic traffic collision time between the CRN and ad-hoc network is minimized subject to an ergodic uplink throughput requirement for the CRN. We focus on real-time implementation of spectrum sharing policy under practical computation and signaling limitations. In our spectrum sharing policy, most computation tasks are accomplished off-line. Hence, little real-time calculation is required which fits the requirement of practical applications. Moreover, the signaling procedure and computation process are designed carefully to reduce the time delay between spectrum sensing and data transmission, which is crucial for enhancing the accuracy of traffic prediction and improving the performance of interference mitigation. The benefits of spectrum sensing and cooperative relay techniques are demonstrated by our numerical experiments.
Performance Analysis of the Matrix Pair Beamformer with Matrix Mismatch
Venue: arXiv cs.IT 2011
Year: 2011

Matrix pair beamformer (MPB) is a blind beamformer. It exploits the temporal structure of the signal of interest (SOI) and applies generalized eigen-decomposition to a covariance matrix pair. Unlike other blind algorithms, it only uses the second order statistics. A key assumption in the previous work is that the two matrices have the same interference statistics. However, this assumption may be invalid in the presence of multipath propagations or certain "smart" jammers, and we call it as matrix mismatch. This paper analyzes the performance of MPB with matrix mismatch. First, we propose a general framework that covers the existing schemes. Then, we derive its normalized output SINR. It reveals that the matrix mismatch leads to a threshold effect caused by "steering vector competition". Second, using matrix perturbation theory, we find that, if there are generalized eigenvalues that are infinite, the threshold will increase unboundedly with the interference power. This is highly probable when there are multiple periodical interferers. Finally, we present simulation results to verify our analysis.
NetInf Mobile Node Architecture and Mobility Management based on LISP Mobile Node
Venue: arXiv cs.NI 2011
Year: 2011

In this paper, we propose an architecture for Network of Information mobile node (NetInf MN). It bears characteristics and features of basic NetInf node architecture with features introduced in the LISP MN architecture. We also introduce a virtual node layer for mobility management in the Network of Information. Therefore, by adopting this architecture no major changes in the contemporary network topologies is required. Thus, making our approach more practical.
Goodput Maximization in Cooperative Networks with ARQ
Venue: arXiv cs.IT 2011
Year: 2011

In this paper, the average successful throughput, i.e., goodput, of a coded 3-node cooperative network is studied in a Rayleigh fading environment. It is assumed that a simple automatic repeat request (ARQ) technique is employed in the network so that erroneously received codeword is retransmitted until successful delivery. The relay is assumed to operate in either amplify-and-forward (AF) or decode-and-forward (DF) mode. Under these assumptions, retransmission mechanisms and protocols are described, and the average time required to send information successfully is determined. Subsequently, the goodput for both AF and DF relaying is formulated. The tradeoffs and interactions between the goodput, transmission rates, and relay location are investigated and optimal strategies are identified.
Inaccessibility-Inside Theorem for Point in Polygon
Venue: arXiv cs.CG 2011
Year: 2011

The manuscript presents a theoretical proof in conglomeration with new definitions on Inaccessibility and Inside for a point S related to a simple or self intersecting polygon P. The proposed analytical solution depicts a novel way of solving the point in polygon problem by employing the properties of epigraphs and hypographs, explicitly. Contrary to the ambiguous solutions given by the cross over for the simple and self intersecting polygons and the solution of a point being multiply inside a self intersecting polygon given by the winding number rule, the current solution gives unambiguous and singular result for both kinds of polygons. Finally, the current theoretical solution proves to be mathematically correct for simple and self intersecting polygons.
Methods for Accelerating Conway's Doomsday Algorithm (part 2)
Venue: arXiv cs.DS 2011
Year: 2011

We propose a modification of a key component in the Doomsday Algorithm for calculating the day of the week of any calendar date. In particular, we propose to replace the calculation of the required term: \lfloor \frac{x}{12} \rfloor + x \bmod 12 + \lfloor \frac{x \bmod 12}{4} \rfloor with -[ \frac{x+11(x \bmod 2)}{2} + 11 (\frac{x+11(x \bmod 2)}{2}\bmod 2)] \bmod 7 for a 2-digit input year x; Although our expression looks daunting and complicated, we will explain why it is actually easy to calculate mentally.
A Path Order for Rewrite Systems that Compute Exponential Time Functions (Technical Report)
Venue: arXiv cs.CC 2011
Year: 2011

In this paper we present a new path order for rewrite systems, the exponential path order EPOSTAR. Suppose a term rewrite system is compatible with EPOSTAR, then the runtime complexity of this rewrite system is bounded from above by an exponential function. Furthermore, the class of function computed by a rewrite system compatible with EPOSTAR equals the class of functions computable in exponential time on a Turing maschine.
Combinatorial Continuous Maximal Flows
Venue: arXiv cs.CV 2011
Year: 2011

Maximum flow (and minimum cut) algorithms have had a strong impact on computer vision. In particular, graph cuts algorithms provide a mechanism for the discrete optimization of an energy functional which has been used in a variety of applications such as image segmentation, stereo, image stitching and texture synthesis. Algorithms based on the classical formulation of max-flow defined on a graph are known to exhibit metrication artefacts in the solution. Therefore, a recent trend has been to instead employ a spatially continuous maximum flow (or the dual min-cut problem) in these same applications to produce solutions with no metrication errors. However, known fast continuous max-flow algorithms have no stopping criteria or have not been proved to converge. In this work, we revisit the continuous max-flow problem and show that the analogous discrete formulation is different from the classical max-flow problem. We then apply an appropriate combinatorial optimization technique to this combinatorial continuous max-flow CCMF problem to find a null-divergence solution that exhibits no metrication artefacts and may be solved exactly by a fast, efficient algorithm with provable convergence. Finally, by exhibiting the dual problem of our CCMF formulation, we clarify the fact, already proved by Nozawa in the continuous setting, that the max-flow and the total variation problems are not always equivalent.
Wireless Scheduling with Power Control
Venue: arXiv cs.NI 2011
Year: 2011

We consider the scheduling of arbitrary wireless links in the physical model of interference to minimize the time for satisfying all requests. We study here the combined problem of scheduling and power control, where we seek both an assignment of power settings and a partition of the links so that each set satisfies the signal-to-interference-plus-noise (SINR) constraints. We give an algorithm that attains an approximation ratio of $O(\log n \cdot \log\log Δ)$, where $n$ is the number of links and $Δ$ is the ratio between the longest and the shortest link length. Under the natural assumption that lengths are represented in binary, this gives the first approximation ratio that is polylogarithmic in the size of the input. The algorithm has the desirable property of using an oblivious power assignment, where the power assigned to a sender depends only on the length of the link. We give evidence that this dependence on $Δ$ is unavoidable, showing that any reasonably-behaving oblivious power assignment results in a $Ω(\log\log Δ)$-approximation. These results hold also for the (weighted) capacity problem of finding a maximum (weighted) subset of links that can be scheduled in a single time slot. In addition, we obtain improved approximation for a bidirectional variant of the scheduling problem, give partial answers to questions about the utility of graphs for modeling physical interference, and generalize the setting from the standard 2-dimensional Euclidean plane to doubling metrics. Finally, we explore the utility of graph models in capturing wireless interference.
Resource-bounded Dimension in Computational Learning Theory
Venue: arXiv cs.CC 2011
Year: 2011

This paper focuses on the relation between computational learning theory and resource-bounded dimension. We intend to establish close connections between the learnability/nonlearnability of a concept class and its corresponding size in terms of effective dimension, which will allow the use of powerful dimension techniques in computational learning and viceversa, the import of learning results into complexity via dimension. Firstly, we obtain a tight result on the dimension of online mistake-bound learnable classes. Secondly, in relation with PAC learning, we show that the polynomial-space dimension of PAC learnable classes of concepts is zero. This provides a hypothesis on effective dimension that implies the inherent unpredictability of concept classes (the classes that verify this property are classes not efficiently PAC learnable using any hypothesis). Thirdly, in relation to space dimension of classes that are learnable by membership query algorithms, the main result proves that polynomial-space dimension of concept classes learnable by a membership-query algorithm is zero.
Optimum Transmission Policies for Battery Limited Energy Harvesting Nodes
Venue: arXiv cs.IT 2011
Year: 2011

Wireless networks with energy harvesting battery powered nodes are quickly emerging as a viable option for future wireless networks with extended lifetime. Equally important to their counterpart in the design of energy harvesting radios are the design principles that this new networking paradigm calls for. In particular, unlike wireless networks considered up to date, the energy replenishment process and the storage constraints of the rechargeable batteries need to be taken into account in designing efficient transmission strategies. In this work, we consider such transmission policies for rechargeable nodes, and identify the optimum solution for two related problems. Specifically, the transmission policy that maximizes the short term throughput, i.e., the amount of data transmitted in a finite time horizon is found. In addition, we show the relation of this optimization problem to another, namely, the minimization of the transmission completion time for a given amount of data, and solve that as well. The transmission policies are identified under the constraints on energy causality, i.e., energy replenishment process, as well as the energy storage, i.e., battery capacity. The power-rate relationship for this problem is assumed to be an increasing concave function, as dictated by information theory. For battery replenishment, a model with discrete packets of energy arrivals is considered. We derive the necessary conditions that the throughput-optimal allocation satisfies, and then provide the algorithm that finds the optimal transmission policy with respect to the short-term throughput and the minimum transmission completion time. Numerical results are presented to confirm the analytical findings.
Joint Scheduling and Resource Allocation in the OFDMA Downlink: Utility Maximization under Imperfect Channel-State Information
Venue: arXiv cs.IT 2011
Year: 2011

We consider the problem of simultaneous user-scheduling, power-allocation, and rate-selection in an OFDMA downlink, with the goal of maximizing expected sum-utility under a sum-power constraint. In doing so, we consider a family of generic goodput-based utilities that facilitate, e.g., throughput-based pricing, quality-of-service enforcement, and/or the treatment of practical modulation-and-coding schemes (MCS). Since perfect knowledge of channel state information (CSI) may be difficult to maintain at the base-station, especially when the number of users and/or subchannels is large, we consider scheduling and resource allocation under imperfect CSI, where the channel state is described by a generic probability distribution. First, we consider the "continuous" case where multiple users and/or code rates can time-share a single OFDMA subchannel and time slot. This yields a non-convex optimization problem that we convert into a convex optimization problem and solve exactly using a dual optimization approach. Second, we consider the "discrete" case where only a single user and code rate is allowed per OFDMA subchannel per time slot. For the mixed-integer optimization problem that arises, we discuss the connections it has with the continuous case and show that it can solved exactly in some situations. For the other situations, we present a bound on the optimality gap. For both cases, we provide algorithmic implementations of the obtained solution. Finally, we study, numerically, the performance of the proposed algorithms under various degrees of CSI uncertainty, utilities, and OFDMA system configurations. In addition, we demonstrate advantages relative to existing state-of-the-art algorithms.